Beddok Arnaud, Grogg Kira, Nioche Christophe, Rozenblum Laura, Orlhac Fanny, Calugaru Valentin, Crehange Gilles, Shih Helen A, Marin Thibault, Buvat Irène, El Fakhri Georges
Inserm LITO U1288, Institut Curie, PSL Research University, University Paris Saclay, Orsay, France.
Yale PET Center Department of Radiology & Biomedical Imaging, Yale University School of Medicine, New Heaven, USA, Connecticut.
Radiol Med. 2025 Aug 20. doi: 10.1007/s11547-025-02072-1.
This study evaluates the efficacy of a previously published [18F]-FDG PET radiomic signature in predicting locoregional failure locations post-reirradiation in head and neck cancer (HNC) patients, using an independent cohort from a different institution.
Among the 66 patients reirradiated for recurrent HNC at Massachusetts General Hospital between 2012 and 2022, 31 underwent pre-reirradiation PET, constituting the external cohort for this analysis. These patients were characterized using the same radiomic features as the original model (Intensity_histogram_min, Kurtosis, Correlation, and Contrast), projected as a supplementary individual onto the published first principal component, and assigned to one of two groups using the published cutoff. The cutoff was then optimized for the external cohort to determine the loss of performance due to technical or population shifts.
Among the 31 patients, 22 experienced a second locoregional failure, distributed between 12 "in-field" and 10 "outside" recurrences. With the original cutoff, the model achieved a BA of 70% and a positive predictive value (PPV) of 86% for detecting "in-field" recurrences. After recalibrating the cutoff, the model achieved a BA of 78% and a PPV of 89%, close to the 84.5% BA obtained in the original article.
The study validates the ability of the previously established PET radiomic signature to predict "in-field" relapses following reRT with a high PPV. These results support the potential of PET radiomics in identifying patients who may benefit from "in-field" dose escalation in reRT schemes. The model is freely available through the user-friendly LIFEx software.
本研究使用来自不同机构的独立队列,评估先前发表的[18F]-FDG PET放射组学特征在预测头颈癌(HNC)患者再照射后局部区域失败位置方面的疗效。
在2012年至2022年间于马萨诸塞州总医院接受复发性HNC再照射的66例患者中,31例在再照射前接受了PET检查,构成了本分析的外部队列。这些患者使用与原始模型相同的放射组学特征(强度直方图最小值、峰度、相关性和对比度)进行表征,作为补充个体投影到已发表的第一主成分上,并使用已发表的临界值分配到两组之一。然后针对外部队列优化临界值,以确定由于技术或人群变化导致的性能损失。
在31例患者中,22例经历了第二次局部区域失败,分布在12例“野内”和10例“野外”复发之间。使用原始临界值,该模型检测“野内”复发的BA为70%,阳性预测值(PPV)为86%。重新校准临界值后,该模型的BA为78%,PPV为89%,接近原始文章中获得的84.5%的BA。
本研究验证了先前建立的PET放射组学特征以高PPV预测再程放疗后“野内”复发的能力。这些结果支持PET放射组学在识别可能从再程放疗方案中的“野内”剂量增加中获益的患者方面的潜力。该模型可通过用户友好的LIFEx软件免费获得。